Testing Composite Hypotheses for Locally Stationary Processes

DOI10.1111/1467-9892.00317zbMath1036.62067OpenAlexW3122808515MaRDI QIDQ4455662

Kenji Sakiyama, Masanobu Taniguchi

Publication date: 16 March 2004

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9892.00317

zbMATH Keywords

Wald testcomposite hypothesesLagrange multiplier testlocally stationary processtime-varying spectral densitytests for stationarityGaussian likelihood ratio test

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Non-Markovian processes: hypothesis testing (62M07) Asymptotic properties of parametric tests (62F05)

Related Items (10)

A frequency domain test for detecting nonstationary time series ⋮ Testing for Stationarity in Multivariate Locally Stationary Processes ⋮ Testing temporal constancy of the spectral structure of a time series ⋮ Simultaneous variable selection and structural identification for time‐varying coefficient models ⋮ Likelihood Ratio Processes under Nonstandard Settings ⋮ Clustering nonlinear, nonstationary time series using BSLEX ⋮ NONPARAMETRIC HYPOTHESIS OF DRIFT FUNCTION IN LOCALLY STATIONARY DIFFUSION MODELS ⋮ Frequency Domain Tests of Semiparametric Hypotheses for Locally Stationary Processes ⋮ Testing Semiparametric Hypotheses in Locally Stationary Processes ⋮ LAN theorem for non-Gaussian locally stationary processes and its applications

Cites Work

• On the Kullback-Leibler information divergence of locally stationary processes
• Linear Statistical Inference and its Applications

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